Quant jobs / Jump Trading

Data Scientist – Post Trade Analytics

A data scientist in Jump's Post-Trade Analytics team, which measures how the firm trades. You work with trading and infrastructure teams in a high-frequency setting.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Analyse post-trade performance with trading teams
Model exchange performance
Quantify how internal applications affect performance
Build anomaly detection for degradation
Improve research frameworks in Python and C++

What they ask for

Required

3+ years of Python for data science
Statistics background
Data intuition and skepticism
Clear communication of analysis
Curiosity about high-frequency trading

Preferred

C++
SQL
Machine learning
Network protocols (IP, UDP, TCP, Ethernet)

Education: Statistics background (level not stated)
Experience: 3+ years of Python programming with a data science focus
Languages and tools: Python
C++
SQL

How to prepare

Analyse a trade-and-quote dataset for execution quality
Build an anomaly detector on latency time series
Learn how exchange protocols and network latency affect trading
Practise SQL and clear written analysis

What to study

The HFT Quantitative Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Jump Trading’s site before applying: requirements, location and pay can change after we check them.

View the posting on Jump Trading’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Jump Trading and doesn’t handle applications.